 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9WVE9 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MAQFPTPFGGSLDIWAITVEERAKHDQQFQSLKPISGFITGDQARNFFFQ 50
51 SGLPQPVLAQIWALADMNKDGRMDQVEFSIAMKLIKLKLQGYQLPPALPP 100
101 VMKQQPAAISSAPAFGIGGMAGMPPLTAVAPVPMGSIPVVGMSPPLVSSV 150
151 PQAAVPPLANGAPPVIQPLPAFAHPAATLPKSSSFSRSGPGSQLNTKLQK 200
201 AQSFDVASAPAAAEWAVPQSSRLKYRQLFNSHDKTMSGHLTGPQARTILM 250
251 QSSLPQAQLASIWNLSDIDQDGKLTAEEFILAMHLIDVAMSGQPLPPVLP 300
301 PEYIPPSFRRVRSGSGMSVISSSSADQRLPEEPSSEDEQQVEKKLPVTFE 350
351 DKKRENFERGNLELEKRRQALLEQQRKEQERLAQLERAEQERKERERQEQ 400
401 ERKRQLELEKQLEKQRELERQREEERRKEIERREAAKRELERQRQLEWER 450
451 NRRQELLTQRNKDQEGIVVLKARRKTLEFELEALNDKKHQLEGKLQDIRC 500
501 RLATQRQEIESTNKSRELRIAEITHLQQQLQESQQMLGRLIPEKQILSDQ 550
551 LKQVQQNSLHRDSLLTLKRALEAKELARQQLREQLDEVEKETRSKLQEID 600
601 VFNNQLKELREIHSKQQLQKQRSIEAERLKQKEQERKSLELEKQKEEGQR 650
651 RVQERDKQWQEHVQQEEQQRPRKPHEEDKLKREDSVKKKEAEERAKPEVQ 700
701 DKQSRLFHPHQEPAKPAQAPWPTTEKGPLTISAQESAKVVYYRALYPFES 750
751 RSHDEITIQPGDIVMVDESQTGEPGWLGGELKGKTGWFPANYAEKIPENE 800
801 IPTPAKPVTDLTSAPAPKLALRETPAPLPVTSSEPSTTPNNWADFSSTWP 850
851 SSTNEKPETDNWDTWAAQPSLTVPSAGQLRQRSAFTPATATGSSPSPVLG 900
901 QGEKVEGLQAQALYPWRAKKDNHLNFNKSDVITVLEQQDMWWFGEVQGQK 950
951 GWFPKSYVKLISGPVRKSTSIDTGPTEAPSSLKRVASPAAKPAIPGEEFV 1000
1001 AMYTYESSEHGDLTFQQGDVIVVTKKDGDWWTGTVGETSGVFPSNYVRLK 1050
1051 DSEGSGTAGKTGSLGKKPEIAQVIASYTATGPEQLTLAPGQLILIRKKNP 1100
1101 GGWWEGELQARGKKRQIGWFPANYVKLLSPGTSKITPTELPKTAVQPAVC 1150
1151 QVIGMYDYTAQNDDELAFSKGQIINVLSKEDPDWWKGEVSGQVGLFPSNY 1200
1201 VKLTTDMDPSQQWCSDLHLLDMLTPTERKRQGYIHELIVTEENYVNDLQL 1250
1251 VTEIFQKPLTESELLTEKEVAMIFVNWKELIMCNIKLLKALRVRKKMSGE 1300
1301 KMPVKMIGDILSAQLPHMQPYIRFCSCQLNGAALIQQKTDEAPDFKEFVK 1350
1351 RLAMDPRCKGMPLSSFILKPMQRVTRYPLIIKNILENTPENHPDHSHLKH 1400
1401 ALEKAEELCSQVNEGVREKENSDRLEWIQAHVQCEGLSEQLVFNSVTNCL 1450
1451 GPRKFLHSGKLYKAKSNKELYGFLFNDFLLLTQITKPLGSSSTDKVFSPK 1500
1501 SNLQYKMYKTPIFLNEVLVKLPTDPSGDEPIFHISHIDRVYTLRAESINE 1550
1551 RTAWVQKIKAASELYIETEKKKREKAYLVRSQRATGIGRLMVNVVEGIEL 1600
1601 KPCRSHGKSNPYCEVTMGSQCHITKTIQDTLNPKWNSNCQFFIRDLEQEV 1650
1651 LCITVFERDQFSPDDFLGRTEIRVADIKKDQGSKGPVTKCLLLHEVPTGE 1700
1701 IVVRLDLQLFDEP 1713
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
What does the NucPred score mean?
| You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper. |
| NucPred score threshold | Specificity | Sensitivity |
| see above | fraction of proteins predicted to be nuclear that actually are nuclear | fraction of true nuclear proteins that are predicted (coverage) |
| 0.10 | 0.45 | 0.88 |
| 0.20 | 0.52 | 0.83 |
| 0.30 | 0.57 | 0.77 |
| 0.40 | 0.63 | 0.69 |
| 0.50 | 0.70 | 0.62 |
| 0.60 | 0.71 | 0.53 |
| 0.70 | 0.81 | 0.44 |
| 0.80 | 0.84 | 0.32 |
| 0.90 | 0.88 | 0.21 |
| 1.00 | 1.00 | 0.02 |
| Sequences which score >= 0.8 with NucPred and which
are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.) |
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